Reinforcement and Mean-Field Games in Algorithmic Trading - Sebastian Jaimungal
Explore reinforcement learning and mean-field games in algorithmic trading, covering deep Q-learning, reinforced deep Kalman filters, and heterogeneous agent interactions with differing beliefs in financial markets.
Contract Theory and Mean Field Games to Inform Epidemic Models
Contract theory and mean field games applied to epidemic control: exploring models with one principal and multiple agents to inform regulatory decisions in continuous and discrete state spaces.
Linear Stochastic Graphon Systems with Q-Noise
Explore linear stochastic graphon systems with Q-noise, extending classical theory to large networks. Learn about LQG control problems, finite rank operators, and Nash Equilibrium approximations in graphon-based systems.
Stochastic Games on Large Graphs in Mean Field and Sparse Regimes
Explore stochastic games on large graphs, focusing on mean field and sparse regimes. Learn about linear-quadratic models, graph-based player interactions, and large-scale asymptotics in dense and sparse scenarios.
Min LQG Games and Collective Discrete Choice Problems in Decision Making
Explore linear quadratic Gaussian games and their applications in social choice dynamics, election patterns, and micro-robotic exploration through mathematical modeling and Nash equilibria analysis.